1. Field of the Invention
The present invention relates to the field of digital pathology and more particularly relates to the assessment of image quality based on complexity and spatial frequencies and the presentation of said assessment using both visual and quantitative results.
2. Related Art
The cornerstone of pathology is the glass microscope slide with its biologic specimen. Traditionally, a pathologist used a conventional microscope to inspect the specimen. The pathologist would navigate the field of view by moving the slide underneath the microscope's lens and increase or decrease the field of view by selecting lenses of different magnifications. To adjust for the variable thickness of a specimen, the pathologist would adjust the focus by moving the optics up and down and modify the brightness by adjusting the light aperture. In this manner, the pathologist interactively adjusts for acceptable image quality.
Similarly, the cornerstone of digital pathology is the digitized microscope slide (“digital slide”), an image file of the entire slide. Digital pathology scans the microscope glass slide at a high magnification, automating the pathologist's actions of focus and dynamic range adjustment as it captures the image and stores the digital slide. The pathologist inspects the digital slide using viewing software. It is critical that the image is scanned without fault because the viewing software simply displays the captured digital slide and cannot re-focus the image or offer dynamic range adjustments. Common problems that plague scanning software include, but are not limited to, out of focus scans and the introduction of scan-hardware related artifacts into images.
Manually reviewing each image for sufficient scan quality is time consuming because a given digital slide image may be very large (e.g., as large as 200K×100K pixels). Additionally, in many cases only an expert may be able to properly judge variations in the quality of a digital slide and these judgments are highly subjective. For example, scan artifacts can make distinct sub-cellular structures apparent in one slide region but difficult to distinguish in a nearby region. Scan artifacts can also change tissue architecture from a crisply patterned texture to a smooth plane. Furthermore, even a properly scanned digital slide may lack sufficient quality for proper analysis and review. Accordingly, there exists a need for a system that is capable of measuring the quality of the digital slide image and identifying scan-related artifacts.